At present in the development of the automatic driving technique, it is especially important to identify target objects (such as vehicles, move agents, tricycles, bicycles or the like) around a vehicle. A more commonly-used way nowadays is to detect targets objects around the vehicle by a LIDAR (such as a LIDAR with 8-line, 16-line, 32-line or 64-line), where the LIDAR emits pulsed laser light to the surroundings, when the pulsed laser light encounter objects, light returns and light point cloud is generated, by which target objects in the surroundings and its size, position and movement velocity could be identified.
At present, the main way of identifying target objects by using laser point clouds is as follows: labeling a received laser point cloud point by point manually in advance to obtain sample data from the laser point cloud corresponding to a target object; performing machine learning on the sample data to obtain an object recognition model; and identifying a target object corresponding to the laser point cloud by using the object recognition model.